Samples are uniformly distributed over the half-open interval
[low,high) (includes low, but excludes high). In other words,
any value within the given interval is equally likely to be drawn
by uniform.

Parameters:

low : float or array_like of floats, optional

Lower boundary of the output interval. All values generated will be
greater than or equal to low. The default value is 0.

high : float or array_like of floats

Upper boundary of the output interval. All values generated will be
less than high. The default value is 1.0.

size : int or tuple of ints, optional

Output shape. If the given shape is, e.g., (m,n,k), then
m*n*k samples are drawn. If size is None (default),
a single value is returned if low and high are both scalars.
Otherwise, np.broadcast(low,high).size samples are drawn.

Convenience function that accepts dimensions as input, e.g., rand(2,2) would generate a 2-by-2 array of floats, uniformly distributed over [0,1).

Notes

The probability density function of the uniform distribution is

anywhere within the interval [a,b), and zero elsewhere.

When high == low, values of low will be returned.
If high < low, the results are officially undefined
and may eventually raise an error, i.e. do not rely on this
function to behave when passed arguments satisfying that
inequality condition.

Examples

Draw samples from the distribution:

>>> s=np.random.uniform(-1,0,1000)

All values are within the given interval:

>>> np.all(s>=-1)True>>> np.all(s<0)True

Display the histogram of the samples, along with the
probability density function: